cleanup

src/pipeline.py

@@ -1,97 +1,3 @@
-# """
-# Complete Multi-Stage MCP Pipeline
-# Orchestrates: Router → Executor → Compiler → Translator
-# """
-
-# import time
-# from typing import Dict, Any
-# from openai import OpenAI
-
-# from .router import QueryRouter
-# from .executor import MCPExecutor, MCP_SERVER_REGISTRY
-# from .compiler import ResponseCompiler
-# from .translator import FarmerTranslator
-
-
-# class FarmerChatPipeline:
-#     """Complete multi-stage MCP pipeline"""
-
-#     def __init__(self, openai_client: OpenAI, location: Dict[str, Any]):
-#         self.location = location
-#         self.router = QueryRouter(openai_client, MCP_SERVER_REGISTRY)
-#         self.executor = MCPExecutor()
-#         self.compiler = ResponseCompiler()
-#         self.translator = FarmerTranslator(openai_client)
-
-#     async def process_query(self, query: str, verbose: bool = False) -> Dict[str, Any]:
-#         """
-#         Process farmer query through complete pipeline
-        
-#         Returns:
-#             {
-#                 "query": str,
-#                 "routing": dict,
-#                 "compiled_data": dict,
-#                 "advice": str,
-#                 "pipeline_time_seconds": float
-#             }
-#         """
-#         if verbose:
-#             print(f"\n🌾 Processing: {query}")
-#             print(f"📍 Location: {self.location['name']}")
-
-#         pipeline_start = time.time()
-
-#         # STAGE 1: Query Routing
-#         if verbose:
-#             print("🎯 Stage 1: Routing...")
-        
-#         routing = self.router.route(query, self.location)
-        
-#         if verbose:
-#             print(f"   → Servers: {', '.join(routing['required_servers'])}")
-
-#         # STAGE 2: MCP Execution (Parallel)
-#         if verbose:
-#             print("⚙️ Stage 2: Executing MCP servers...")
-        
-#         raw_results = await self.executor.execute_parallel(
-#             routing['required_servers'],
-#             self.location['lat'],
-#             self.location['lon']
-#         )
-        
-#         if verbose:
-#             print(f"   → Completed in {raw_results['execution_time_seconds']}s")
-
-#         # STAGE 3: Response Compilation
-#         if verbose:
-#             print("🔗 Stage 3: Compiling results...")
-        
-#         compiled = self.compiler.compile(raw_results)
-        
-#         if verbose:
-#             print(f"   → {compiled['completeness']}")
-
-#         # STAGE 4: Farmer Translation
-#         if verbose:
-#             print("🌾 Stage 4: Generating advice...")
-        
-#         farmer_advice = self.translator.translate(query, compiled, self.location)
-
-#         pipeline_time = time.time() - pipeline_start
-
-#         if verbose:
-#             print(f"✅ Complete! Total: {pipeline_time:.2f}s\n")
-
-#         return {
-#             "query": query,
-#             "routing": routing,
-#             "compiled_data": compiled,
-#             "advice": farmer_advice,
-#             "pipeline_time_seconds": round(pipeline_time, 2)
-#         }
-
 """
 Farmer.chat Pipeline - Main Orchestrator
 Coordinates Router → Executor → Compiler stages for alert generation